The 3rd Generation Partnership Project (3GPP) is responsible for the standardization of the Universal Mobile Telecommunication System (UMTS) and Long Term Evolution (LTE). The 3GPP work on LTE is also referred to as Evolved Universal Terrestrial Access Network (E-UTRAN). LTE is a technology for realizing high-speed packet-based communication that can reach high data rates both in the downlink and in the uplink, and is thought of as a next generation mobile communication system relative to UMTS. In order to support high data rates, LTE allows for a system bandwidth of 20 MHz, or up to 100 MHz when carrier aggregation is employed. LTE is also able to operate in different frequency bands and can operate in at least Frequency Division Duplex (FDD) and Time Division Duplex (TDD) modes.
LTE uses orthogonal frequency-division multiplexing (OFDM) in the downlink and discrete-Fourier-transform-spread (DFT-spread) OFDM in the uplink. The basic LTE physical resource can be seen as a time-frequency grid, as illustrated in FIG. 1, where each time-frequency resource element (TFRE) corresponds to one subcarrier during one OFDM symbol interval, on a particular antenna port. There is one resource grid per antenna port. The resource allocation in LTE is described in terms of resource blocks, where a resource block corresponds to one slot in the time domain and 12 contiguous 15 kHz subcarriers in the frequency domain. Two time-consecutive resource blocks represent a resource block pair, which corresponds to the time interval upon which scheduling operates.
An antenna port is a “virtual” antenna, which is defined by an antenna port-specific reference signal (RS). An antenna port is defined such that the channel over which a symbol on the antenna port is conveyed can be inferred from the channel over which another symbol on the same antenna port is conveyed. The signal corresponding to an antenna port may possibly be transmitted by several physical antennas, which may also be geographically distributed. In other words, an antenna port may be transmitted from one or several transmission points. Conversely, one transmission point may transmit one or several antenna ports. Antenna ports may interchangeably be referred to as “RS ports”.
Multi-antenna techniques can significantly increase the data rates and reliability of a wireless communication system. The performance is in particular improved if both the transmitter and the receiver are equipped with multiple antennas, which results in a multiple-input multiple-output (MIMO) communication channel. Such systems and/or related techniques are commonly referred to as MIMO.
The LTE standard is currently evolving with enhanced MIMO support. A core component in LTE is the support of MIMO antenna deployments and MIMO related techniques. LTE Release 10 and above (also referred to as LTE-Advanced) enables support of eight-layer spatial multiplexing with possibly channel dependent precoding. Such spatial multiplexing is aimed for high data rates in favorable channel conditions. An illustration of precoded spatial multiplexing is provided in FIG. 2.
As seen, the information carrying symbol vector s is multiplied by an NT×r precoder matrix WNT×r, which serves to distribute the transmit energy in a subspace of the NT dimensional vector space, where NT corresponds to the number of antenna ports. The r symbols in s each are part of a symbol stream, a so-called layer, and r is referred to as the transmission rank. In this way, spatial multiplexing is achieved since multiple symbols can be transmitted simultaneously over the same TFRE. The number of layers, r, is typically adapted to suit the current channel properties.
Furthermore, the precoder matrix is often selected from a codebook of possible precoder matrices, and typically indicated by means of a precoder matrix indicator (PMI), which for a given rank specifies a unique precoder matrix in the codebook. If the precoder matrix is confined to have orthonormal columns, then the design of the codebook of precoder matrices corresponds to a Grassmannian subspace packing problem.
The received NR×1 vector yn on the data TFRE indexed n is modeled byyn=HnWNT×rsn+en  (1)                where en is a noise plus interference vector modeled as realizations of a random process. The precoder for rank r, WNT×r, can be a wideband precoder, which is either constant over frequency, or frequency selective.        
The precoder matrix is often chosen to match the characteristics of the NR×NT MIMO channel H, resulting in so-called channel dependent precoding. When based on UE feedback, this is commonly referred to as closed-loop precoding and essentially strives for focusing the transmit energy into a subspace which is strong in the sense of conveying much of the transmitted energy to the UE. In addition, the precoder matrix may also be selected to strive for orthogonalizing the channel, meaning that after proper linear equalization at the UE, the inter-layer interference is reduced.
In closed-loop precoding, the UE transmits, based on channel measurements in the forward link, or downlink, recommendations to the base station, which in LTE is called the evolved NodeB (eNodeB) of a suitable precoder to use. A single precoder that is supposed to cover a large bandwidth (wideband precoding) may be fed back. It may also be beneficial to match the frequency variations of the channel and instead feed back a frequency-selective precoding report, e.g. several precoders, one per subband. This is an example of the more general case of channel state information (CSI) feedback, which also encompasses feeding back other entities than precoders to assist the eNodeB in subsequent transmissions to the UE. Thus, channel state information may include one or more of PMI, channel quality indicators (CQIs) or rank indicator (RI).
Signal and channel quality estimation is a fundamental part of a modern wireless system. Noise and interference estimates are used not only in the demodulator, but are also important quantities when estimating, for example, the channel quality indicator (CQI), which is typically used for link adaptation and scheduling decisions on the eNodeB side.
The term en in (1) represents noise and interference in a TFRE and is typically characterized in terms of second order statistics such as variance and correlation. The interference can be estimated in several ways including from the cell-specific reference symbols (RS) that are present in the time-frequency grid of LTE. Such RS may correspond to the Rel-8 cell-specific RS, CRS (antenna ports 0-3), which are illustrated in FIG. 3, as well as the new CSI RS available in Rel-10, which will be described in more detail below. CRS are sometimes also referred to as common reference signals.
Estimates of interference and noise can be formed in various ways. Estimates can easily be formed based on TFREs containing cell specific RS since sn and WNT×r are then known and Hn is given by the channel estimator. It is further noted that the interference on TFREs with data that is scheduled for the UE in question can also be estimated as soon as the data symbols, sn are detected, since at that moment they can be regarded as known symbols. The latter interference can alternatively also be estimated based on second order statistics of the received signal and the signal intended for the UE of interest, thus possibly avoiding needing to decode the transmission before estimating the interference term. Alternatively the interference can be measured on TFREs where the desired signal is muted, so the received signal corresponds to interference only. This has the advantage that the interference measurement may be more accurate and the UE processing becomes trivial because no decoding or desired signal subtraction need to be performed.
Channel State Information Reference Signal (CSI-RS)
In LTE Release-10, a new reference symbol sequence, the CSI-RS, was introduced for the purpose of estimating channel state information. The CSI-RS provides several advantages over basing the CSI feedback on the cell-specific reference symbols (CRS) which were used for that purpose in previous releases. Firstly, the CSI-RS is not used for demodulation of the data signal, and thus does not require the same density. In other words, the overhead of the CSI-RS is substantially less. Secondly, CSI-RS provides a much more flexible means to configure CSI feedback measurements. For example, which CSI-RS resource to measure on can be configured in a UE specific manner. Moreover, the support of antenna configurations larger than 4 antennas must resort to CSI-RS, since the CRS is only defined for at most 4 antennas.
By measuring on a CSI-RS a UE can estimate the effective channel the CSI-RS is traversing including the radio propagation channel, antenna gains, and any possible antenna virtualizations. A CSI-RS port may be precoded so that it is virtualized over multiple physical antenna ports; that is, the CSI-RS port can be transmitted on multiple physical antenna ports, possibly with different gains and phases. In more mathematical rigor this implies that if a known CSI-RS signal xn is transmitted, a UE can estimate the coupling between the transmitted signal and the received signal, i.e. the effective channel. Hence if no virtualization is performed in the transmission:yn=Hnxn+en 
the UE can measure the effective channel Heff=Hn. Similarly, if the CSI-RS is virtualized using a precoder WNT×r asyn=HnWNT×rxr+en the UE can estimate the effective channel Heff=HnWNT×r.
Related to CSI-RS is the concept of zero-power CSI-RS resources (also known as a muted CSI-RS) that are configured just as regular CSI-RS resources, so that a UE knows that the data transmission is mapped around those resources. The intent of the zero-power CSI-RS resources is to enable the network to mute the transmission on the corresponding resources as to boost the SINR of a corresponding non-zero power CSI-RS, possibly transmitted in a neighbor cell/transmission point. For Rel-11 of LTE, a special zero-power CSI-RS that a UE is mandated to use for measuring interference plus noise is under discussion. As the name indicates, a UE can assume that the TPs of interest are not transmitting on the muted CSI-RS resource and the received power can therefore be used as a measure of the interference plus noise level.
Based on a specified CSI-RS resource and an interference measurement configuration, e.g. a muted CSI-RS resource, the UE can estimate the effective channel and noise plus interference, and consequently also determine which rank, precoder and transport format to recommend that best match the particular channel.
Power Measurement Offset
As mentioned above, in LTE a terminal provides the network with channels state information, by means of recommending a particular transmission for a measured effective channel, for example a combination of PMI, RI, and a CQI. To enable this recommendation the UE needs to know the relative power offset between the reference signals (that are used for measuring the effective channel), and a hypothesized upcoming data transmission. In the following we refer to such a power offset as a power measurement offset (PMO). This power offset is tied to a specific reference signal, for example, it relates to the parameter Pc which is part of the configuration message for setting up a measurement on a CSI-RS, or to the parameter nomPDSCH-RS-EPRE-Offset for CRS.
In practice, CQIs are rarely perfect and substantial errors might be present which means that the estimated channel quality does not correspond to the actual channel quality seen for the link over which the transmission takes place. The eNodeB can to some extent reduce the detrimental effects of erroneous CQI reporting by means of outer-loop adjustment of the CQI values. By monitoring the ACK/NACK signaling of the hybrid ARQ, the eNodeB can detect if the block error rate (BLER), or a related measure, is below or above the target value. Using this information, the eNodeB can decide to use more offensive (or defensive) MCS than recommended by the UE. However, outer loop control is a crude tool for improving link adaptation and the convergence of the loops can be slow.
Also, it is more difficult for the eNodeB to deviate from recommended rank, because the CQI reports relates directly to the rank. A change in rank therefore renders the information provided by the CQI reports difficult or impossible to utilize—that is, the eNodeB would have severe difficulties knowing which MCS to use on the different data streams if the eNodeB would override the rank recommended by the UE.
The network can improve the rank reporting by adjusting a PMO in the UE. For example, if the power measurement offset is decreased (causing the terminal to assume a lower power for the transmitted data channel), the terminal will tend to recommend a lower rank since the “optimal” rank is increasing with SINR.
Coordinated Multipoint Transmission (CoMP)
CoMP transmission and reception refers to a system where the transmission and/or reception at multiple, geographically separated antenna sites is coordinated in order to improve system performance. More specifically, CoMP refers to coordination of antenna arrays that have different geographical coverage areas. In the subsequent discussion we refer to a set of antennas covering essentially the same geographical area in the same manner as a point, or more specifically as a Transmission Point (TP). Thus, a point might correspond to one of the sectors at a site, but it may also correspond to a site having one or more antennas all intending to cover a similar geographical area. Often, different points represent different sites. Antennas correspond to different points when they are sufficiently geographically separated and/or have antenna diagrams pointing in sufficiently different directions. Although the present disclosure focuses mainly on downlink CoMP transmission, it should be appreciated that in general, a transmission point may also function as a reception point. The coordination between points can either be distributed, by means of direct communication between the different sites, or by means of a central coordinating node. A further coordination possibility is a “floating cluster” where each transmission point is connected to, and coordinates, a certain set of neighbors (e.g. two neighbors). A set of points that perform coordinated transmission and/or transmission is referred to as a CoMP coordination cluster, a coordination cluster, or simply as a cluster in the following.
FIG. 5 shows an example wireless network with a CoMP coordination cluster comprising three transmission points, denoted TP1, TP2 and TP3.
CoMP is a tool introduced in LTE to improve the coverage of high data rates, the cell-edge throughput and/or to increase system throughput. In particular, the goal is to distribute the user perceived performance more evenly in the network by taking control of the interference in the system, either by reducing the interference and/or by better prediction of the interference.
CoMP operation targets many different deployments, including coordination between sites and sectors in cellular macro deployments, as well as different configurations of Heterogeneous deployments, where for instance a macro node coordinates the transmission with pico nodes within the macro coverage area.
There are many different CoMP transmission schemes that are considered; for example,
Dynamic Point Blanking where multiple transmission points coordinates the transmission so that neighboring transmission points may mute the transmissions on the time-frequency resources (TFREs) that are allocated to UEs that experience significant interference.
Coordinated Beamforming where the TPs coordinate the transmissions in the spatial domain by beamforming the transmission power in such a way that the interference to UEs served by neighboring TPs are suppressed.
Dynamic Point Selection where the data transmission to a UE may switch dynamically (in time and frequency) between different transmission points, so that the transmission points are fully utilized.
Joint Transmission where the signal to a UE is simultaneously transmitted from multiple TPs on the same time/frequency resource. The aim of joint transmission is to increase the received signal power and/or reduce the received interference, if the cooperating TPs otherwise would serve some other UEs without taking our JT UE into consideration.
CoMP Feedback
A common denominator for the CoMP transmission schemes is that the network needs CSI information not only for the serving TP, but also for the channels linking the neighboring TPs to a terminal. By, for example, configuring a unique CSI-RS resource per TP, a UE can resolve the effective channels for each TP by measurements on the corresponding CSI-RS. Note that the UE is likely unaware of the physical presence of a particular TP, it is only configured to measure on a particular CSI-RS resource, without knowing of any association between the CSI-RS resource and a TP.
A detailed example showing which resource elements within a resource block pair may potentially be occupied by UE-specific RS and CSI-RS is provided in FIG. 4. In this example, the CSI-RS utilizes an orthogonal cover code of length two to overlay two antenna ports on two consecutive REs. As seen, many different CSI-RS patterns are available. For the case of 2 CSI-RS antenna ports, for example, there are 20 different patterns within a subframe. The corresponding number of patterns is 10 and 5 for 4 and 8 CSI-RS antenna ports, respectively.
A CSI-RS resource may be described as the pattern of resource elements on which a particular CSI-RS configuration is transmitted. One way of determining a CSI-RS resource is by a combination of the parameters “resourceConfig”, “subframeConfig”, and “antennaPortsCount”, which may be configured by RRC signaling.
Several different types of CoMP feedback are possible. Most alternatives are based on per CSI-RS resource feedback, possibly with CQI aggregation of multiple CSI-RS resources, and also possibly with some sort of co-phasing information between CSI-RS resources. The following is a non-exhaustive list of relevant alternatives (note that a combination of any of these alternatives is also possible):
Per CSI-RS resource feedback corresponds to separate reporting of channel state information (CSI) for each of a set of CSI-RS resources. Such a CSI report may, for example, comprise one or more of a Precoder Matrix Indicator (PMI), Rank Indicator (RI), and/or Channel Quality Indicator (CQI), which represent a recommended configuration for a hypothetical downlink transmission over the same antennas used for the associated CSI-RS, or the RS used for the channel measurement. More generally, the recommended transmission should be mapped to physical antennas in the same way as the reference symbols used for the CSI channel measurement.
Typically there is a one-to-one mapping between a CSI-RS and a TP, in which case per CSI-RS resource feedback corresponds to per-TP feedback; that is, a separate PMI/RI/CQI is reported for each TP. Note that there could be interdependencies between the CSI reports; for example, they could be constrained to have the same RI. Interdependencies between CSI reports have many advantages, such as; reduced search space when the UE computes feedback, reduced feedback overhead, and in the case of reuse of RI there is a reduced need to perform rank override at the eNodeB.
The considered CSI-RS resources are configured by the eNodeB as the CoMP Measurement Set. In the example shown in FIG. 5, different measurement sets may be configured for wireless devices 540 and 550. For example, the measurement set for wireless device 540 may consist of CSI-RS resources transmitted by TP1 and TP2, since these points may be suitable for transmission to device 540. The measurement set for wireless device 550 may instead be configured to consist of CSI-RS resources transmitted by TP2 and TP3. The wireless devices will report CSI information for the transmission points corresponding to their respective measurement sets, thereby enabling the network to e.g. select the most appropriate transmission point for each device.
Aggregate feedback corresponds to a CSI report for a channel that corresponds to an aggregation of multiple CSI-RS. For example, a joint PMI/RI/CQI can be recommended for a joint transmission over all antennas associated with the multiple CSI-RS.
A joint search may however be too computationally demanding for the UE, and a simplified form of aggregation is to evaluate an aggregate CQI which are combined with per CSI-RS resource PMIs, which should typically all be of the same rank corresponding to the aggregated CQI or CQIs. Such a scheme also has the advantage that the aggregated feedback may share much information with a per CSI-RS resource feedback. This is beneficial, because many CoMP transmission schemes require per CSI-RS resource feedback, and to enable eNodeB flexibility in dynamically selecting CoMP scheme, aggregated feedback would typically be transmitted in parallel with per CSI-RS resource feedback. To support coherent joint transmission, such per CSI-RS resource PMIs can be augmented with co-phasing information enabling the eNodeB to rotate the per CSI-RS resource PMIs so that the signals coherently combine at the receiver.
Interference Measurements for CoMP
For efficient CoMP operation it is equally important to capture appropriate interference assumptions when determining the CSI as it is to capture the appropriate received desired signal.
For the purpose of this disclosure, a CSI process is defined as the reporting process of CSI (e.g., CQI and potentially associated PMI/RI) for a particular effective channel, and an interference measurement resource. Optionally, a CSI process may also be associated with one or more interference emulation configurations, as will be explained below. The effective channel is defined by a reference signal resource comprising one or multiple associated reference sequences. The interference measurement resource is a set of resource elements in which one or more signals that are assumed to be interfering with the desired signal are received. The IMR may correspond to a particular CQI reference resource, e.g. a CRS resource. Alternatively, the IMR may be a resource configured specifically for measuring interference.
In uncoordinated systems the UE can effectively measure the interference observed from all other TPs (or all other cells), which will be the relevant interference level in an upcoming data transmission. Such interference measurements are typically performed by analyzing the residual interference on CRS resources, after the UE subtracts the impact of the CRS signal. In coordinated systems performing CoMP such interference measurements becomes increasingly irrelevant. Most notably, within a coordination cluster an eNodeB can to a large extent control which TPs that interfere a UE in any particular TFRE. Hence, there will be multiple interference hypotheses depending on which TPs are transmitting data to other terminals.
For the purpose of improved interference measurements new functionality is introduced in LTE Release 11, where the agreement is that the network will be able to configure which particular TFREs that is to be used for interference measurements for a particular UE; this is defined as an interference measurement resource (IMR). The network can thus control the interference seen on a IMR, by for example muting all TPs within a coordination cluster on the associated TFREs, in which case the terminal will effectively measure the inter CoMP cluster interference. In the example shown in FIG. 5, this would correspond to muting TP1, TP2 and TP3 in the TFREs associated with the IMR.
Consider for example a dynamic point blanking scheme, where there are at least two relevant interference hypotheses for a particular UE: in one interference hypothesis the UE sees no interference from the coordinated transmission point; and in the other hypothesis the UE sees interference from the neighboring point. To enable the network to effectively determine whether or not a TP should be muted, the network may configure the UE to report two, or generally multiple CSIs corresponding to different interference hypotheses—that is, there can be two CSI processes corresponding to different interference situations. Continuing the example of FIG. 5, assume that the wireless device 550 is configured to measure CSI from TP3. However, TP2 may potentially interfere with a transmission from TP2, depending on how the network schedules the transmission. Thus, the network may configure the device 550 with two CSI processes for TP3 (or, more specifically, for measuring the CSI-RS transmitted by TP3). One CSI process is associated with the interference hypothesis that TP2 is silent, and the other CSI process corresponds to the hypothesis that TP3 is transmitting an interfering signal.
To facilitate such a scheme it has been proposed to configure multiple IMRs, wherein the network is responsible for realizing each relevant interference hypothesis in the corresponding IMR. Hence, by associating a particular IMR with a particular CSI process, relevant CSI information, e.g. CQI, can be made available to the network for effective scheduling. In the example of FIG. 5, the network may, for example, configure one IMR in which only TP2 is transmitting, and another IMR in which TP2 and TP3 are both silent. Each CSI process may then be associated with a different IMR.
Although the possibility of associating a CSI process with one or more IMRs enables the network to obtain a better basis for making link adaptation and scheduling decisions, there is still room for further improvement when determining channel state information. In particular, there is a need for improved mechanisms of estimating interference for a particular CSI process.